Researchers, scientists, and companies use data technologies to make new scientific discoveries and innovations. The purpose is to improve the life of billions of people worldwide. High-performance computing (HPC) provides a basis for scientific, research-based, and industrial advancements.
An HPC cluster is a network of multiple compute servers. Depending on the application requirements, a cluster may consist of thousands of servers. Each server in an HPC cluster is called a node. These nodes work in parallel to increase processing speed and maximize the system’s performance.
Bear in mind that companies deploy HPC clusters on-premises or in the cloud. A standard HPC cluster has three node types: the entry node, the storage node, and the worker node. These nodes form connections to perform a specific task.
For example, the entry node, also known as the user login, allows users to use the cluster. Likewise, the storage nodes store data permanently. The worker nodes run programs in the HPC environment. These nodes don’t have local storage space. Read on!
A head node is an essential component of the HPC cluster that acts as the launching point for running different jobs on the cluster. It is a configured system that acts as a mediator between the internal components and outside networks. According to Clovertex HPC experts, the head node is the central managing server that provides workload and scheduling for jobs across the HPC cluster.
Data Transfer Node
As the name indicates, data transfer nodes perform the transportation of data across the cluster. These are dedicated systems designed, configured, and deployed for data transfer over HPC networks.
Compute nodes are the actual nodes of the HPC cluster that performs the entire task. Not only does it perform the computational work, but a management node also provisions it in the cluster. Bear in mind that the workload management systems defined the number of slots on a compute node in the HPC.
Fat Compute Nodes
Fat node is another component of the HPC cluster that uses a “CCNUMA” architecture. These nodes make the memory visible and accessible to and from the CPU. The hardware components handle the cache coherency. In addition, fat node features single-node performance at high-speed with maximum memory capacity, leading to reliability, efficiency, and optimal results.
A GPU node is a vital component of the HPC system’s cluster. It involves equipping each node with a graphic processing unit. As a result, the HPC system performs faster calculations using a GPU cluster or node by harnessing graphics processing units’ high power and speed.
Designing an HPC cluster requires an individual or company to choose the correct hardware, allocate power, space, and cooling, head node installation, monitoring and management, and run benchmarks and applications.
It is crucial to understand the components of HPC clusters to streamline and optimize the system’s performance. If you want to maximize efficiency, achieve better results, and reduce costs, contact Clovertex today!